Journal of Theoretical & Computational Science : Citations & Metrics Report
Articles published in Journal of Theoretical & Computational Science have been cited by esteemed scholars and scientists all around the world. Journal of Theoretical & Computational Science has got h-index 11, which means every article in Journal of Theoretical & Computational Science has got 11 average citations.
Following are the list of articles that have cited the articles published in Journal of Theoretical & Computational Science.
2021 | 2020 | 2019 | 2018 | 2017 | |
---|---|---|---|---|---|
Year wise published articles |
32 | 21 | 2 | 0 | 11 |
Year wise citations received |
61 | 83 | 45 | 37 | 22 |
Journal total citations count | 385 |
Journal impact factor | 3.48 |
Journal 5 years impact factor | 5.01 |
Journal cite score | 4.07 |
Journal h-index | 11 |
Journal h-index since 2019 | 9 |
Important citations (283)
prediction of joint space narrowing progression in knee osteoarthritis patients |
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Ai msk clinical applications: cartilage and osteoarthritis |
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Validation of knee kl-classifying deep neural network with finnish patient data |
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A novel hybrid approach based on deep cnn features to detect knee osteoarthritis |
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Predisposition for knee osteoarthritis in portuguese adults with obesity |
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Comparison of machine learning methods for predicting modified total shape score in x-ray radiography |
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Integrating dynamic simulation modeling to assess pathophysiology of arthritis |
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Deep learning for knee osteoarthritis diagnosis and progression prediction from plain radiographs and clinical data |
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Deepoa: clinical decision support system for early detection and severity grading of knee osteoarthritis |
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Deep learning improves predictions of the need for total knee replacement |
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can additional patient information improve the diagnostic performance of deep learning for the interpretation of knee osteoarthritis severity |
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A comparative analysis of automatic classification and grading methods for knee osteoarthritis focussing on x-ray images |
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Identifying robust risk factors for knee osteoarthritis progression: an evolutionary machine learning approach |
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Machine learning-based automatic classification of knee osteoarthritis severity using gait data and radiographic images |
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A machine learning pipeline for predicting joint space narrowing in knee osteoarthritis patients |
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The use of artificial intelligence in the evaluation of knee pathology |
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Prediction of pain in knee osteoarthritis patients using machine learning: data from osteoarthritis initiative |
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Identification of risk factors and machine learning-based prediction models for knee osteoarthritis patients |
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A lightweight cnn and joint shape-joint space (js2) descriptor for radiological osteoarthritis detection |
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Feature learning to automatically assess radiographic knee osteoarthritis severity |
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